Fraud in many industries, including, for example, the financial services industry, has become increasingly sophisticated. While concerned industries continue to develop and deploy anti-fraud measures, fraudsters continually create strategies to evade the anti-fraud measures.
Fraud rule development is critical to the current fraud prevention environment. A key factor of successful fraud rule development is a rapid reaction to the most recent fraud trend, thereby quickly detecting the new fraud trend and preventing fraud attempts based on the new fraud trend in order to reduce fraud loss over time.
Existing procedures of building fraud rule strategies for fraud channels are manual with multiple human interactions. Fraud analysts look for potential fraud trends using several separate fraud reports, individually pulling data for identified target sections, segments, divisions, or areas, exploring data in more detail and potentially further conducting data analytics through multi-dimensional division and selecting key fraud drivers/attributes for rule/strategy development. After the rule/strategy is developed, analysts send the rule strategy to management for approval and to information technology experts for implementation.
The above-described process is time consuming. The process may require an extensive time period, during which the fraud attack will be ongoing. Fraudsters are rational, and will not continue to attempt transactions that are declined. While the existing technology has the capability to recognize recurring fraud patterns, the constant adaptation by fraudsters provides the fraudsters with a speed advantage over the currently existing lengthy rule development cycles.
Accordingly, an opportunity exists to significantly enhance fraud rule development efficiency by introducing a dynamic, configurable, and industry-leading framework that automates the short-term combat with fraudsters. The system should be equipped to quickly capture existing and emerging fraud attacks at a relatively granular level and create effective fraud rules to combat most recent fraud trend. The system should further enable comprehensive fraud trend monitoring and enforce effectiveness of fraud rule development.